Search Results
Working Paper
Local Projections
A central question in applied research is to estimate the effect of an exogenous intervention or shock on an outcome. The intervention can affect the outcome and controls on impact and over time. Moreover, there can be subsequent feedback between outcomes, controls and the intervention. Many of these interactions can be untangled using local projections. This method’s simplicity makes it a convenient and versatile tool in the empiricist’s kit, one that is generalizable to complex settings. This article reviews the state-of-the art for the practitioner, discusses best practices and ...
Working Paper
Climate Change and the Geography of the U.S. Economy
This paper examines how the spatial distribution of people and jobs in the United States has been and will be impacted by climate change. Using novel county-level weather data from 1951 to 2020, we estimate the longer-run effects of weather on local population, employment, wages, and house prices using a panel distributed lag model. The historical results point to long-lasting negative effects of extreme temperatures on each of these outcomes. We highlight that a long lag structure is necessary to appropriately capture the longer-run effects of climate change, as short-run effects are often ...
Working Paper
Mean Group Distributed Lag Estimation of Impulse Response Functions in Large Panels
This paper develops Mean Group Distributed Lag (MGDL) estimation of impulse responses of common shocks in large panels with one or two cross-section dimensions. We derive sufficient conditions for asymptotic normality, and document satisfactory small sample performance using Monte Carlo experiments. Three empirical illustrations showcase the usefulness of MGDL estimators: crude oil price pass-through to U.S. city- and product-level retail prices; retail price effects of U.S. monetary policy shocks; and house price effects of U.S. monetary policy shocks.
Working Paper
Mean Group Distributed Lag Estimation of Impulse Response Functions in Large Panels
This paper develops Mean Group Distributed Lag (MGDL) estimation of impulse responses in large panels with one or two cross-section dimensions. Sufficient conditions for asymptotic consistency and asymptotic normality are derived, and satisfactory small sample performance is documented using Monte Carlo experiments. MGDL estimators are used to estimate the effects of crude oil price increases on U.S. city- and product-level retail prices.
Working Paper
Analysis of Multiple Long Run Relations in Panel Data Models with Applications to Financial Ratios
This paper provides a new methodology for the analysis of multiple long-run relations in panel data models where the cross-section dimension, n, is large relative to the time-series dimension, T. For panel data models with large n, researchers have focused on panels with a single long-run relationship. The main difficulty has been to eliminate short-run dynamics without generating significant uncertainty for identification of the long run. We overcome this problem by using non-overlapping sub-sample time averages as deviations from their full-sample counterpart and estimating the number of ...
Working Paper
Local Projections for Applied Economics
The dynamic causal effect of an intervention on an outcome is of paramount interest to applied macro- and micro-economics research. However, this question has been generally approached differently by the two literatures. In making the transition from traditional time series methods to applied microeconometrics, local projections can serve as a natural bridge. Local projections can translate the familiar language of vector autoregressions (VARs) and impulse responses into the language of potential outcomes and treatment effects. There are gains to be made by both literatures from greater ...
Journal Article
Where Do the Wealthiest Get Their Wealth?
An analysis using data from Norway identifies the top 0.1% of wealth accumulators and then traces how their wealth evolved from their 20s to their 50s.
Report
Approximating Grouped Fixed Effects Estimation via Fuzzy Clustering Regression
We propose a new, computationally-efficient way to approximate the “grouped fixed-effects” (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the regularization parameter m approaches 1, the fuzzy clustering objective converges to the GFE objective; moreover, we recast this objective as a standard Generalized Method of Moments problem. We replicate the empirical results of Bonhomme and Manresa (2015) and show that our estimator delivers almost identical ...
Working Paper
Estimating Taxable Income Responses with Elasticity Heterogeneity
We extend a standard taxable income model with its typical functional-form assumptions to account for nonlinear budget sets. We propose a new method to estimate taxable income elasticity that is more policy relevant than the typically estimated elasticity based on linearized budget sets. Using U.S. data from the NBER tax panel for 1979-1990 and differencing methods, we estimate an elasticity of 0.75 for taxable income and 0.20 for broad income. These estimates are higher than those obtained by specifications based on linearization. Our approach offers a new way to address the problem of ...